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Project
EvoSym: (ERA-Net Complexity-Net) Oorsprong en evolutie van biologische symbool systemen. (Emergence and Evolution of Biological Symbol Systems). (FWOAL575)
EvoSym is a collaborative European research project supported under
the Complexity-NET 2009 pilot funding call, Interdisciplinary
Challenges for Complexity Science. Complexity-NET is the European
Network for the Coordination of Complexity Research and Training
Activities.
The project applies methods and techniques of complexity science to
understand the emergence and evolution of biological "symbol systems"
(also called "biosemiotic systems"), such as genetic coding
(DNA-protein), RNA editing, cell signalling, etc. It also investigates
potential technological applications in distributed agent-based
software and robotics. It aims two anser two key questions:
(1) How do complex representational and communicative coding
systems emerge, self-organise and evolve, from micro to macro levels,
in the natural biosphere? and
(2) How can this biological understanding be applied to the
artificial evolution of complex coding systems in computational and/or
robotic systems?
The project is further structured into three major work packages:
WP1 builds on previous work in modelling prebiotic molecular evolution
in spatially extended individual-based systems. It specifically
considers whether or how "RNA coding" could evolve in such an
environment (Lead partner: Bioinformatics Group, Universiteit
Utrecht).
WP2 is a complementary investigation of the origin and evolution of
evolvable coding and translation in purely computational systems -
specifically "coreworlds" (e.g., tierra , nanopond etc.) and
"artificial chemistries", which can model evolving software agents in
networked computer systems (Lead partner: Artificial Life Lab, Rince
Institute.)
WP3 bridges between the other two workpackages, to apply principles of
language evolution in collective robotic systems to the emergence of
complex (i.e., compositional and grammatical) languages in models of
chemical communication among biological cells. (Lead partner:
Artificial Intelligence Laboratory, Vrije Universiteit Brussel.)
the Complexity-NET 2009 pilot funding call, Interdisciplinary
Challenges for Complexity Science. Complexity-NET is the European
Network for the Coordination of Complexity Research and Training
Activities.
The project applies methods and techniques of complexity science to
understand the emergence and evolution of biological "symbol systems"
(also called "biosemiotic systems"), such as genetic coding
(DNA-protein), RNA editing, cell signalling, etc. It also investigates
potential technological applications in distributed agent-based
software and robotics. It aims two anser two key questions:
(1) How do complex representational and communicative coding
systems emerge, self-organise and evolve, from micro to macro levels,
in the natural biosphere? and
(2) How can this biological understanding be applied to the
artificial evolution of complex coding systems in computational and/or
robotic systems?
The project is further structured into three major work packages:
WP1 builds on previous work in modelling prebiotic molecular evolution
in spatially extended individual-based systems. It specifically
considers whether or how "RNA coding" could evolve in such an
environment (Lead partner: Bioinformatics Group, Universiteit
Utrecht).
WP2 is a complementary investigation of the origin and evolution of
evolvable coding and translation in purely computational systems -
specifically "coreworlds" (e.g., tierra , nanopond etc.) and
"artificial chemistries", which can model evolving software agents in
networked computer systems (Lead partner: Artificial Life Lab, Rince
Institute.)
WP3 bridges between the other two workpackages, to apply principles of
language evolution in collective robotic systems to the emergence of
complex (i.e., compositional and grammatical) languages in models of
chemical communication among biological cells. (Lead partner:
Artificial Intelligence Laboratory, Vrije Universiteit Brussel.)
Date:1 Jan 2010 → 31 Dec 2011
Keywords:Programming, Informatics, Artificial Intelligence, Www
Disciplines:Mathematical sciences and statistics